Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11287227 | PMC |
| http://dx.doi.org/10.1148/rycan.240171 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
An analysis of multilevel factor contributions to breast cancer screening inequities in an academic health system.
Cancer
February 2025
General Medicine Service, VA Puget Sound Health Care System, Seattle, Washington, USA.
Background: Breast cancer screening (BCS) inequities are evident at national and local levels, and many health systems want to address these inequities, but may lack data about contributing factors. The objective of this study was to inform health system interventions through an exploratory analysis of potential multilevel contributors to BCS inequities using health system data.
Methods: The authors conducted a cross-sectional analysis within a large academic health system including 19,774 individuals who identified as Black (n = 1445) or White (n = 18,329) race and were eligible for BCS.
[Analysis of Factors That Promote Awareness of Breast MRI Surveillance for Carriers of Hereditary Breast Cancer Risk Genes ( BRCA1/2)].
Nihon Hoshasen Gijutsu Gakkai Zasshi
January 2025
Department of Risk Analysis and Biodosimetry, Institute of Radiation Emergency Medicine, Hirosaki University.
Purpose: Hereditary breast and ovarian cancers (HBOC) carry a high risk of breast cancer, and detailed screening with contrast-enhanced breast MRI (breast MRI surveillance) is recommended. With the increase in the number of individuals diagnosed with HBOC, the demand for breast MRI surveillance is also rising. However, the current system is inadequate, with factors such as lack of knowledge and indifference among healthcare professionals, and insufficient understanding of breast MRI surveillance being cited.
View Article and Find Full Text PDFA quantum-optimized approach for breast cancer detection using SqueezeNet-SVM.
Sci Rep
January 2025
College of Information Science and Technology, Hainan Normal University, Haikou, 571158, China.
Breast cancer is one of the most aggressive types of cancer, and its early diagnosis is crucial for reducing mortality rates and ensuring timely treatment. Computer-aided diagnosis systems provide automated mammography image processing, interpretation, and grading. However, since the currently existing methods suffer from such issues as overfitting, lack of adaptability, and dependence on massive annotated datasets, the present work introduces a hybrid approach to enhance breast cancer classification accuracy.
View Article and Find Full Text PDFMyofibroblastoma of the breast mimicking carcinoma: a diagnostic challenge with a crucial role for histopathology and immunohistochemistry.
BMJ Case Rep
January 2025
Pathology, Shri B.M. Patil Medical College Hospital and Research Centre, BLDE (Deemed to be University), Vijayapura, Karnataka, India.
Myofibroblastoma is a rare mesenchymal tumour known for its benign nature but complex diagnostic pathway. A woman in her 40s presented with a painless breast mass, initially reported as a fibroadenoma on ultrasound mammography and as a benign to borderline phyllodes tumour on fine needle aspiration cytology. Contrast-enhanced CT was reported as carcinoma of the breast with Breast Imaging and Reporting Data System (BIRADS)-6.
View Article and Find Full Text PDFXGBoost Enhances the Performance of SAFE: A Novel Microwave Imaging System for Early Detection of Malignant Breast Cancer.
Cancers (Basel)
January 2025
Mitos Medical Technologies, ITU Ayazaga Ari 1, Maslak, 34469 Istanbul, Turkey.
Background/objectives: Breast cancer is a significant global health concern, and early detection is crucial for improving patient outcomes. Mammography is widely used but has limitations, particularly for younger women with denser breasts. These include reduced sensitivity, false positives, and radiation risks.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!